Delineation of suitable sites for groundwater recharge based on groundwater potential with RS, GIS, and AHP approach for Mand catchment of Mahanadi Basin

Groundwater management requires a systematic approach since it is crucial to the long-term viability of livelihoods and regional economies all over the world. There is insufficient groundwater management and difficulties in storage plans as a result of increased population, fast urbanisation, and climate change, as well as unpredictability in rainfall frequency and intensity. Groundwater exploration using remote sensing (RS) data and geographic information system (GIS) has become a breakthrough in groundwater research, assisting in the assessment, monitoring, and conservation of groundwater resources. The study region is the Mand catchment of the Mahanadi basin, covering 5332.07 km2 and is located between 21°42′15.525″N and 23°4′19.746″N latitude and 82°50′54.503″E and 83°36′1.295″E longitude in Chhattisgarh, India. The research comprises the generation of thematic maps, delineation of groundwater potential zones and the recommendation of structures for efficiently and successfully recharging groundwater utilising RS and GIS. Groundwater Potential Zones (GPZs) were identified with nine thematic layers using RS, GIS, and the Multi-Criteria Decision Analysis (MCDA) method. Satty's Analytic Hierarchy Process (AHP) was used to rank the nine parameters that were chosen. The generated GPZs map indicated regions with very low, low to medium, medium to high, and very high groundwater potential encompassing 962.44 km2, 2019.92 km2, 969.19 km2, and 1380.42 km2 of the study region, respectively. The GPZs map was found to be very accurate when compared with the groundwater fluctuation map, and it is used to manage groundwater resources in the Mand catchment. The runoff of the study area can be accommodated by the computing subsurface storage capacity, which will raise groundwater levels in the low and low to medium GPZs. According to the study results, various groundwater recharge structures such as farm ponds, check dams and percolation tanks were suggested in appropriate locations of the Mand catchment to boost groundwater conditions and meet the shortage of water resources in agriculture and domestic use. This study demonstrates that the integration of GIS can provide an efficient and effective platform for convergent analysis of various data sets for groundwater management and planning.

www.nature.com/scientificreports/ Data acquisition. Slope, geology, rainfall, drainage density, soil, geomorphology, lineament, land use land cover (LULC), and curvature were all analysed to establish a GPZs for the study area. The Digital Elevation Model (DEM) was obtained from the United States Geological Survey (USGS) (http:// www. earth explo rer. usgs. gov) of the Shuttle Radar Topography Mission (SRTM) as 1 arc-second (approx. 30 m resolution). The DEM was used to delineate the catchment, sub-catchments boundary, slope, drainage and drainage density using various spatial analytic tools in ArcGIS software. The geology, geomorphology, lineament data, well location data, pre-monsoon and post-monsoon water level data were collected from Central Groundwater Board (CGWB) and runoff from Central Water Commission (CWC), (Bhubaneswar). The Inverse Distance Weightage (IDW) approach from ArcGIS 10.5 was used to generate the spatial distribution of rainfall map for the year of 2021 75 . Details of all the input data is mentioned in Table 1. The cloud-free sentinel-2 imagery was used to prepare the LULC map with supervised classification methods in ArcGIS 10.5.
Analytic hierarchy process. The GIS-based MCDA-AHP techniques was used in the present study, which involve and transforms geographical data (input) into the decision (output), where qualitative information on particular themes and attributes is turned into quantitative values by generating a pair comparison matrix using Saaty's scale 51 . Each thematic layers were rated between 1/6 and 4 based on the impacts of these thematic levels  www.nature.com/scientificreports/ and their characteristics on groundwater occurrences ( Table 2). A higher score indicates a greater impact on groundwater resources. The scores are diagonally arranged in a Pairwise Comparison Matrix, which has an equal number of rows and columns. The value "1" is diagonally positioned in the matrix, running from the centre to the corner (Table 3). The paired assessment of parameters in the AHP could often result in certain inconsistency. To assess this, the consistency ratio (CR) was used, and it determined by using the random index scale 51 and the acquired eigenvalues from the comparison matrix (Eq. 1) (Table 4). 51 proposed the concept of CR to quantify the amount of consistency of the weight of the parameters. It's the ratio of the consistency index (CI) (Eq. 2) to the random consistency index (RI). The CR is used to demonstrate the correctness of the weights found in the Normalized Pairwise Comparison Matrix (NPCM).   where, n = number of factors and λmax = average value of the consistency vector. For a given judgement matrix, a CR value of less than 0.1 is acceptable, and RI is the random index, which is the consistency index of a randomly generated Pairwise Comparison Matrix 11 .
The thematic layers, as well as the sub-criteria weight, were determined and analysed by using a Pairwise Comparison Matrix. The score is assigned to sub-criteria on a scale of 1 to 4 based on favourable conditions and their relevance in detecting the groundwater zone. The most acceptable sub-criteria received a maximum score 4, the least suitable sub-parameters received a minimum score 1, and moderately suitable sub-parameters of the criterion for GPZ identification received an intermediate value ( Table 5).
The thematic layers are then reclassed using the weightage values obtained after being transformed to 30 × 30 m cell size. The weighted overlay analysis (WOA) is a technique that allows users to address spatially complicated site suitability concerns using common measures of several inputs and accordingly GZPs were identified. In the WOA tool, all reclassified raster maps overlayed and accordingly weights were assigned. Finally, the cell score of each input raster is multiplied by the weighted values of each raster layer (Eq. 3). The generated raster layer was divided into four groups of GPZs with the same range of given weights based on the United Nations' Food and Agricultural Organization (FAO) recommendations.
where, S is total GPZ score, wi denotes weight of GPZ criteria, xi Indicates sub-criteria score of i GPZ criteria, and n represents total number of GPZ criteria.
Finally, the overlay analysis is used to generate the groundwater potential map, which is then validated using fluctuation data. Figure 2 depicts the methodological flowchart of the present study.
Appropriate locations for artificial recharge structures. The artificial recharge structures were suggested based on the topography, land-use class, slope, aspect, and soil type 76 . In the present study, the artificial recharge structures (percolation tank, check dam and farm pond) have been proposed based on the recommendations of the Indian National Committee on Hydrology (INCOH) 76 . To select the suitable structures, the different selection criterias like dimensions and its applications were discussed in Tables 6 and 7.
Estimation of available volume of subsurface storage. The total volume of subsurface storage was estimated based on the thickness of unsaturated zone (within 10 mbgl). And it was assumed that the volume of unsaturated strata which will recharge and store the groundwater will be 40% of the total volume of subsurface storage 77 . Availability of surplus water for recharge. Surplus runoff was account as 40% of the total runoff generated from Mand catchment for the artificial recharge of aquifers 77 . Research involving human participants and/or animals. This article does not contain any studies involving animals performed by any of the authors. This article does not contain any studies involving human participants performed by any of the authors.

Results and discussion
Drainage density map. The drainage density (DD) of the study was estimated by using the total stream length (11,651.15 km), and the total catchment area. From the analysis it was observed that the study area was having a total of 20,203 streams. The DD of the study area were ranges from 0.75 to 4 km/km 2 . Further, the DD was divided into four classes as extremely high (3-4 km/km 2 ), high (2-3 km/km 2 ), medium (1-2 km/km 2 ), and low (0-1 km/km 2 ) (Fig. 3). A total of 58% of the area falls into the low (0-1 km/km 2 ) DD category, and 12% of area falls into the very high (3-4 km/km 2 ) DD category. In the present study, higher weights were assigned to low DD regions and lower weights were assigned to high DD regions. The Low DD indicates more rain water infiltration and contributes to groundwater potential, whereas higher values of DD indicate the high surface runoff and less infiltration 62 .
Rainfall map. Rainfall is the principal source of groundwater recharge in the study area, and almost 85% of it receives during the southwest monsoon season. The rate of infiltration of runoff water is directly affected by rainfall distribution and slope gradient, increasing the probability of potential groundwater zones. The annual rainfall of the study area was ranges from 1291 to 1734 mm, and further it was divided into five classes as very low (1200-1300 mm), low (1300-1400 mm), moderate (1400-1500 mm), high (1500-1600 mm), and very high (1600-1750 mm) 45 Fig. 4). In the present study, the high rainfall classes were given a high weight of 4, and vice versa for the AHP analysis. In the study region, the northern part receives the least amount of rainfall (about 20% of the total area), whereas the southern part receives highest amount of rainfall.
Slope map. The slope of the study area was divided into six categoriesas level (0%), nearly level (0-2%), very gently sloping (2-4%), gently sloping (4-6%), slightly moderate sloping (6-8%), moderately sloping (8-10%), strongly sloping (10-14%), steep sloping (14-16%) and very steep sloping (> 16%) (Fig. 6). The slope map of the catchment illustrates a complicated topography with undulations and uneven slopes. The majority of the watershed contains almost flat to moderately sloping fields, which can be regarded excellent groundwater recharge sites since surface water has more time to infiltrate and accordingly higher weights were given. The catchment has a region with strong to severe slope, which is bad for groundwater recharge as surface water does not have time to infiltrate through the soil surface.
Geology map. The type of groundwater occurrences and their distribution is heavily influenced by geology.
The Mand catchment's predominant geology is Gondwana rocks, 46% of its area followed by Chhotanagpur gneissic complex (26%) and Chhattisgarh supergroup, which includes the Raigarh and Chandrapur formations (15.25%) (Fig. 7). Talchir, Barakar, Kamthi and Mahadeva formation are the Gondwana rocks of the region.    www.nature.com/scientificreports/ The Barakar Formation covers the majority of Gondwana (32.85%) followed by Kamthi (7.47%) ( Table 9). The Barakar is the study area's only coal-bearing deposit both in the shallow and deeper zones. Kamthi are the newest members and are mostly represented by sandstones and shales which are iron-rich and filthy to brownish in colour. The Talchir formation's lithology include shale, sandstone, and boulder bed. Because Gondwana is made up of sediments, it is assigned the highest weighting because of the increased likelihood of groundwater occurrences owing to its lithology. The crystalline and metamorphic rocks, which are part of the Chhotanagpur gneissic complex, are mostly found at the northern edge of the region. The gneissic rocks of Chhotanagpur are mostly quartz mica schist and quartzite with granite gneiss, intruded by granite and dolerite 72 . They are given the least weight because of their lithology, which has a low water transmissivity.
The phreatic aquifer in the Chhattisgarh supergroup was given moderate weighting since the area is good for groundwater development due to its good production potential.
Geomorphology map. Geomorphology is the important element for understanding the presence, potential, and flow of groundwater resources due to its tectonic activity and denudational processes. The structural plains on Gondwana rocks covers 46% of the area followed by pediment/ pediplains (26%) and structural plains and plateaus on proterozoic rocks (21%) dominates the Mand catchment (Fig. 8). The structural plains on Gondwana rocks have been assigned the greatest weighting; due to its sedimentary origin, it serves as an outstanding groundwater recharge source 6 . The pediment/ pediplain complex located in the north-eastern and southern parts of the catchment which is made up of weathered colluvium material or gravel; it serves as a significant groundwater recharge source in the catchment and is thus given more weightage.
The structural plains and plateaus on proterozoic rocks covers southern and eastern portion respectively are given moderate weightage due to the high transmission rates of alluvium deposits on a gentle slope and are www.nature.com/scientificreports/ frequently connected with well potentials. The least weighted value was provided to the denudational plateau on magnetic and metamorphic rocks since they have more surface runoff than recharge due to poor water transmission.

Lineament map.
A lineament is a linear feature i.e., fault and fracture in a landscape that represents the geological structure beneath it. Lineaments enhances secondary porosity and permeability that are crucial in terms of hydrogeology because they provide pathways for groundwater circulation 40 (Fig. 9). As a result, these characteristics define the GPZs 58 . The possibility of a potential groundwater area decreases with decreasing lineament number and increases with increasing number of lineaments 57 . Due to extensive lineaments, the lineament map suggests that the southern and western parts of the study region are very appropriate for groundwater recharge. Based on lineaments density, the northern and some central parts of the state have less potential for groundwater recharge since density declines from the south to the centre and then to the north. Table 10 lists the different lineament structures as well as their corresponding lengths.  www.nature.com/scientificreports/   Table 11) Forests and scrubland predominate in the upper part of the catchment, whereas the middle and lower part of catchment having predominately agricultural land, settlement and water bodies. The land use land cover was validated using google satellite image, ground truthing data, and kappa coefficient. The kappa   www.nature.com/scientificreports/ coefficient (Kp) was calculated based on the method discussed by other researchers 78,79 . The Kappa coefficient ranges from 0 to 1, and a higher coefficient value indicates more accuracy 80,81 .
In overall the agricultural land covers almost 58.14% of the total catchment area, which is followed by the scrubland and fallow land. The classification's overall accuracy was found to be 89.25%, and the Kappa coefficient to be 0.91. The Chhattisgarh districts of Bastar, Dhamtari and Korba observed similar outcomes [82][83][84] .
Amongst the all LULC, water bodies were given the highest score as 4 since in the research region carry a substantial volume of water throughout the year. Similarly, agricultural land and dense forest area was also given highest score as 4 as the roots of the trees loosen the soil and increased the water holding capacity and percolation. Fallow land, barren land, and settlement were given moderate to low score as 3 to 1 based on its water transmission and water holding capacity.
Curvature. The curvature of hill slopes, which represents the morphology of the regional topography, is a significant factor to consider in the case of groundwater hydrology and terrain instability. It is the shape of the surface profile, which might be concave, linear, or convex 40 . The shapes and curvatures of a slope have a strong influence on the dynamics of surface and subsurface hydrology, as well as the development and accumulation of soil. In comparison to convex slopes, the soil thickness is greater on concave slopes. Because surface and subsurface water collect on the concave slope, increasing pore water pressure during storms and severe downpours, it is given more weight for groundwater potential. A quick runoff occurs on a convex slope, avoiding water storage and resulting in less weight given to groundwater potential. Convex slopes include intervening hills and side slopes. Concave features include erosional landforms such as gullies. Planar landforms are those that fall between the concave and convex slope categories. In the Mand catchment, the curvature values range from 8.51 to + 9.08 and the Fig. 11 is depicting curvature map of the area. A positive curvature value indicates that the surface is convex, whereas a negative curvature value indicates that the slope is concave. Linear surfaces are given the value zero.
Identification of groundwater potential zones. The above mentioned nine parameters were considered for identification of groundwater potential zones. These parameters were used in the AHP approach and accordingly weights were assigned based on the Pairwise Comparison Matrix. The CR and CI was found as 0.05 and 0.094, respectively for high GPZs.
The groundwater potential zones (GPZs) of the study area were divided into four groups such as Low, low to medium, medium to high, and extremely high GPZs, which covers the area of 18.05, 37.88, 18.18, and 25.89%, respectively (Fig. 12, Table 12). The very high potential zone was found in the areas like Kharsia, Raigarh, Korba, and some parts of Dharamjaigarh block, and the low GPZs were found in Lundra, Batauli, Pathalgaon, Sitapur blocks. Due to the availability of loamy textured well-drained soil, high intensity of rainfall, presence of lineament, gentle slope, concave curvature, favourable geological formation, and vast agricultural land with excellent infiltration capability, the results show that the excellent GPZ was concentrated in the southern, western, and

Validation
The validation of the estimated GPZs was done by comparing them with the groundwater fluctuation map calculated using observation well (Fig. 13) data obtained from the Central Groundwater Board's observation well data (CGWB). In this study, a total of 79 observation wells data were taken into the consideration. The groundwater fluctuation map was generated by using pre-monsoon (April) and post-monsoon (December) mbgl (metre below ground level) water level data (Fig. 14a,b). In general, areas with greater water level fluctuation have low groundwater potential, while those with less water level fluctuation typically have high groundwater potential 45,62 .
During the pre-monsoon season the groundwater table fluctuates from 1.9 to 19.95 mbgl, with an average of 10.40 mbgl, this may be due to the extraction of groundwater for irrigation. The shallowest water table depth was found in the southern part of the catchment, while the deep-water table depth is found in the western part. The groundwater table fluctuates during the post monsoon was ranges from 2.09 and 18.30 mbgl, with an average of 6.42 mbgl. From the groundwater fluctuation map, it was observed that the pathalgaon block has the deepest water depth, whereas Dabhara and Pusaur have the shallowest depth. The groundwater fluctuation map (Fig. 15) shows that the southern and some north-western parts of the study area have low groundwater fluctuation, indicating high water potential zone. Whereas the western and some central parts of the study area have more water table fluctuations, indicating low groundwater potential zone. The scatter plots in Fig. 16 reveal a negative  www.nature.com/scientificreports/ relationship between groundwater fluctuation and groundwater potential. From the study result it can infer that the groundwater potential map is very accurate when compared to groundwater fluctuation maps and may be utilised for groundwater resource management in the Mand catchment. It was discovered that wells in low GPZs had a water yield capability of 10-50 L per minute (lpm). whereas in medium, medium to high, and high GPZs, had the water yield capacity as 50-100 lpm, and 100-200 lpm, respectively. It can be inferred from the study that the GIS and AHP-based methodologies for delineating GPZs used here are a viable way for river basin-based planning and development in tropical and sub-tropical regions with a variety of geo-environmental scenarios.

Development of management plan for low and low to medium groundwater potential areas
The high groundwater potential zone implies that the availability or bearing capacity of capacity of groundwater is high in the area. And the management plan is needed for the low and low to medium potential zones for development or recharging of groundwater. The type of structures to be constructed for groundwater management was selected based on the GPZs map, depth to water level map, and topography of the study area. Different structures like percolation tanks, check dams, and farm ponds were proposed for artificial recharge and storing of water in the low and low to medium GPZs. Total number of percolation tanks, check dams, and farm ponds as 36, 39, and 21, respectively (Fig 17).
In the Mand catchment, the volume of unsaturated strata that will recharge and store groundwater is 21.33 km 3 , or 40% of the total subsurface storage 77 . The total amount of runoff generated by the Mand catchment was account as 5.07 km 3 . Out of the total runoff 2.03 km 3 (40%) was deemed as excess for artificial recharge 77 . This predicted runoff can be accommodated by the computed subsurface storage capacity, which will raise groundwater levels in the low and low to medium GPZs.

Conclusion
The current study assessed the groundwater potential using AHP and GIS methodologies in the agriculture dominated Mand catchment in the middle Mahanadi Basin. To map the GPZs of the research region, nine criteria were weighted and overlaid into the ArcGIS 10.5 environment: geology, geomorphology, curvature, slope, LULC, drainage density, lineament, soil, and rainfall. The groundwater potential shows that 37.88% of the area is in the low to medium potential zone, 18.18% is in the medium to high potential zone, 25.89% is in the very high potential zone covering the southern and western parts, and only 18.05% is in the very low GPZs covering the northern and north-western parts.
The research considers initiatives to manage extensive water usage by seasonal surface water storage and recharging it with seasonal runoff, as well as modification of irrigation methods in places with low and low to medium potential recharge. The runoff of the study area can be accommodated by the computing subsurface www.nature.com/scientificreports/ storage capacity, which will raise groundwater levels in the low and low to medium GPZs. The computed subsurface storage capacity (21.33 km 3 or 40% of the total subsurface storage area) can accommodate the runoff (2.03 km 3 or 40% of total runoff), raising groundwater levels in the low and low to medium GPZs. According to the www.nature.com/scientificreports/ study results, various groundwater recharge structures such as farm ponds, check dams and percolation tanks were suggested in appropriate locations of the Mand catchment to boost groundwater conditions and meet the shortage of water resources in agriculture and domestic use. Total number of percolation tanks, check dams, and farm ponds as 36, 39, and 21, respectively. Since agricultural land comprises up the majority of the study area, this research will help to enhance the irrigation system and increase the region's agricultural production. This study demonstrates that the integration of GIS can provide an efficient and effective platform to planners and decision makers for proper groundwater management and planning through convergent analysis of various data sets.